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Full-Text Articles in Engineering
Predictive Modeling Of A Buoyancy-Operated Cooling Tower Under Unsaturated Conditions: Adjoint Sensitivity Model And Optimal Best-Estimate Results With Reduced Predicted Uncertainties, Federico Di Rocco, Dan Gabriel Cacuci
Predictive Modeling Of A Buoyancy-Operated Cooling Tower Under Unsaturated Conditions: Adjoint Sensitivity Model And Optimal Best-Estimate Results With Reduced Predicted Uncertainties, Federico Di Rocco, Dan Gabriel Cacuci
Faculty Publications
Nuclear and other large-scale energy-producing plants must include systems that guarantee the safe discharge of residual heat from the industrial process into the atmosphere. This function is usually performed by one or several cooling towers. The amount of heat released by a cooling tower into the external environment can be quantified by using a numerical simulation model of the physical processes occurring in the respective tower, augmented by experimentally measured data that accounts for external conditions such as outlet air temperature, outlet water temperature, and outlet air relative humidity. The model’s responses of interest depend on many model parameters including …
Predictive Modeling Of A Paradigm Mechanical Cooling Tower Model: Ii. Optimal Best-Estimate Results With Reduced Predicted Uncertainties, Ruixian Fang, Dan Gabriel Cacuci, Madalina Badea
Predictive Modeling Of A Paradigm Mechanical Cooling Tower Model: Ii. Optimal Best-Estimate Results With Reduced Predicted Uncertainties, Ruixian Fang, Dan Gabriel Cacuci, Madalina Badea
Faculty Publications
This work uses the adjoint sensitivity model of the counter-flow cooling tower derived in the accompanying PART I to obtain the expressions and relative numerical rankings of the sensitivities, to all model parameters, of the following model responses: (i) outlet air temperature; (ii) outlet water temperature; (iii) outlet water mass flow rate; and (iv) air outlet relative humidity. These sensitivities are subsequently used within the “predictive modeling for coupled multi-physics systems” (PM_CMPS) methodology to obtain explicit formulas for the predicted optimal nominal values for the model responses and parameters, along with reduced predicted standard deviations for the predicted model parameters …